Evolution of Virus-Host Interactions

病毒与宿主相互作用的演变

• 批准号: 8847847
• 负责人: John Yin
• 金额: $ 6.77万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-12-03 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8847847
• 关键词: Acquired Immunodeficiency Syndrome; Address; Advanced Development; Basic Science; Cell physiology; Cells; Common Cold; Computer Simulation; Data; Disease; Environment; Evolution; Exhibits; Gene Order; Goals; Growth; Health; Hepatitis; Human; Infection; Influenza; Integration Host Factors; Knowledge; Laboratories; Learning; Malignant Neoplasms; Measures; Medical; Methodology; Methods; Modeling; Molecular; Molecular Models; Nature; Oncolytic; Organism; Population; Process; Protein Biosynthesis; Relative (related person); Research; Resources; Rest; Serial Passage; Structure; Systems Biology; Therapeutic; Time; Variant; Vesicular stomatitis Indiana virus; Viral; Virus; Virus Diseases; Virus-Cell Membrane Interaction; Work; base; cancer therapy; design; fighting; fitness; human disease; insight; molecular modeling; mutant; novel vaccines; predictive modeling; research study; therapy development; tumor; virus host interaction

DESCRIPTION (provided by applicant): Viruses pose a significant threat to human health based on their ability to cause diseases such as AIDS, influenza, hepatitis, cancer and the common cold. Basic research has revealed much about the molecular details of processes that are essential for viruses to reproduce, but a critical barrier to further progress is a lack of understanding of how factors of the host environment quantitatively impact virus growth. The proposed research aims to address this barrier by advancing new quantitative experiments and computational models of virus growth. The approach will employ, combine and extend perspectives drawn from the fields of experimental evolution and systems biology. Specific aims of the proposed project will be to: (1) advance computational models of virus growth to provide an integrated dynamic measure of cellular resource use, (2) quantify how resource use is altered during evolutionary adaptation of virus to host cells, and (3) elucidate mechanisms by which viral adaptation alters resource use. The methodology established by this research will set a basis for advancing the development of data-driven predictive models of virus growth. Results of the research will have the potential to significantly impact several fields: the design anti-viral therapeutics, applications of viruses in oncolytic (anti-tumor) cancer therapies, and development of new vaccines. At a more basic level, predictive models of virus growth will be useful for better understanding how viruses grow, evolve and persist in Nature.

描述（由申请人提供）：病毒会根据引起艾滋病，流感，肝炎，癌症和普通感冒等疾病的能力对人类健康构成重大威胁。基础研究已经揭示了有关病毒繁殖至关重要的过程的分子细节，但是进一步进步的关键障碍是缺乏对宿主环境因素如何定量影响病毒生长的理解。拟议的研究旨在通过推进病毒生长的新定量实验和计算模型来解决这一障碍。该方法将采用，结合和扩展从实验进化和系统生物学领域中得出的观点。拟议项目的具体目的是：（1）病毒生长的预先计算模型，以提供综合的细胞资源使用动态度量，（2）量化病毒对宿主细胞的进化适应过程中如何改变资源的使用，以及（3）阐明病毒适应性的机制。这项研究建立的方法将为发展数据驱动的病毒生长预测模型的发展树立基础。该研究的结果将有可能显着影响几个领域：设计抗病毒疗法，病毒在溶瘤（抗肿瘤）癌症疗法中的应用以及新疫苗的开发。在更基本的层面上，病毒生长的预测模型将有助于更好地理解病毒在本质上的生长，发展和持久。